Argon2 Hash Generator

Understanding Argon2 Parameters

Memory Cost

Memory cost determines how much RAM is required to compute the hash. Higher memory makes parallel attacks more expensive. OWASP recommends at least 64 MB for web applications. For high-security applications, consider 128 MB or higher.

Time Cost (Iterations)

Time cost controls the number of iterations over the memory. More iterations mean slower hashing, which increases security but also increases login latency. A value of 3 is typically recommended for web applications.

Parallelism

Parallelism sets the number of threads used for hashing. Higher parallelism can speed up hashing on multi-core systems but also increases the attack surface. A value of 4 is commonly used.

Hash Length

The output hash length in bytes. 32 bytes (256 bits) is sufficient for most applications and provides ample security margin.

Salt

A salt is random data added to the password before hashing. It ensures that identical passwords produce different hashes, preventing rainbow table attacks. Always use a unique, random salt for each password. This tool can auto-generate a secure salt or let you specify a custom one.

How to Use This Argon2 Hash Generator

1. Choose your mode: Select Generate Hash to create a new hash, or Verify Hash to check if a password matches an existing hash.
2. Enter your password: Type or paste the password or text you want to hash into the input field.
3. Select Argon2 variant: Choose Argon2id (recommended), Argon2i (side-channel resistant), or Argon2d (GPU resistant) based on your security needs.
4. Configure parameters: Set memory cost (64 MB recommended), time cost (3 iterations recommended), parallelism (4 threads recommended), and hash length (32 bytes recommended).
5. Generate hash: Click Generate Hash to create your Argon2 hash. Copy the encoded or hex output for your application.

Recommended Parameters by Use Case

Can I Decrypt an Argon2 Hash?

No. Argon2 is a one-way hash function, meaning it is computationally infeasible to reverse the hash back to the original password. This is by design - it protects passwords even if the hash database is compromised.

To verify a password, hash the input with the same parameters and salt, then compare the result to the stored hash. The encoded Argon2 format includes all necessary parameters, making verification straightforward.

Frequently Asked Questions

What is Argon2 and why is it recommended?

Argon2 is a modern password hashing algorithm that won the Password Hashing Competition in 2015. It is designed to be resistant to GPU and ASIC attacks by requiring significant memory and computation. Argon2 is recommended by OWASP and NIST for password storage in 2025 and beyond.

What are the differences between Argon2i, Argon2d, and Argon2id?

Argon2d is optimized to resist GPU attacks and is faster but vulnerable to side-channel attacks. Argon2i is designed to resist side-channel attacks and is suitable for password hashing on shared systems. Argon2id is a hybrid that provides both protections and is the recommended choice for most applications.

What parameters should I use for Argon2?

For most web applications, use Argon2id with 64 MB memory cost, 3 iterations, and 4 threads. For high-security applications like password managers, consider 128 MB or higher memory cost and 4+ iterations. The goal is approximately 500ms hash time on your server.

Can I decrypt an Argon2 hash?

No, Argon2 is a one-way hash function. It is computationally infeasible to reverse the hash back to the original password. To verify a password, hash the input with the same parameters and compare the result to the stored hash.

What is a salt and why is it important?

A salt is random data added to the password before hashing. It ensures that identical passwords produce different hashes, preventing rainbow table attacks and making it harder to crack multiple passwords at once. Always use a unique, random salt for each password.

References

• Argon2 - Wikipedia
• Argon2 Specification (PDF)
• OWASP Password Storage Cheat Sheet
• Argon2 Reference Implementation (GitHub)